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Flexible Online Task Assignment in Real-Time Spatial Data

Summary: Defines Flexible Two-sided Online task Assignment (FTOA) for real-time spatial data, guiding idle workers via predicted task/worker distributions to boost matches. Two-step framework combines offline prediction with POLAR-OP online assignment; achieves 0.47-competitive ratio and O(1) per-event processing, validated on synthetic and real taxi data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h5e3b1c5b9f21bc19
Venue
VLDB
Year
2017
Pagerank
4.9793485e-05
Overall Rank
12,295 | 17.34%
DOI
10.14778/3137628.3137643

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Authors

BibTeX Citation

@article{tong_vldb17,
        title = {{Flexible Online Task Assignment in Real-Time Spatial Data}},
        author = {Tong, Yongxin and Wang, Libin and Zhou, Zimu and Ding, Bolin and Chen, Lei and Ye, Jieping and Xu, Ke},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {11},
        pages = {1334},
        doi = {10.14778/3137628.3137643},
        url = {https://doi.org/10.14778/3137628.3137643},
        year = {2017}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2,367 Capacity Constrained Assignment in Spatial Databases 2008 SIGMOD 8.5623448e-05
2,406 On Efficient Spatial Matching 2007 VLDB 8.5169461e-05
2,829 A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing 2014 VLDB 7.9629265e-05
4,759 Online Minimum Matching in Real-Time Spatial Data: Experiments and Analysis 2016 VLDB 6.4316584e-05
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